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Semantic communication has gained attention as a key enabler for intelligentand context-aware communication. However, one of the key challenges of semanticcommunications is the need to tailor the resource allocation to meet thespecific requirements of semantic transmission. In this paper, we focus onnetworks with limited resources where devices are constrained to transmit withlimited bandwidth and power over large distance. Specifically, we devise anefficient strategy to select the most pertinent semantic features andparticipating users, taking into account the channel quality, the transmissiontime, and the recovery accuracy. To this end, we formulate an optimizationproblem with the goal of selecting the most relevant and accurate semanticfeatures over devices while satisfying constraints on transmission time andquality of the channel. This involves optimizing communication resources,identifying participating users, and choosing specific semantic information fortransmission. The underlying problem is inherently complex due to itsnon-convex nature and combinatorial constraints. To overcome this challenge, weefficiently approximate the optimal solution by solving a series of integerlinear programming problems. Our numerical findings illustrate theeffectiveness and efficiency of our approach in managing semanticcommunications in networks with limited resources.

Semantic-Aware Resource Allocation in Constrained Networks with Limited User Participation